Method and device for identifying boundary and determining fracture characteristics, equipment and medium

Abstract

The invention belongs to the technical field of geophysical exploration, and provides a boundary identification and fracture feature determination method, device, equipment and medium, and the method comprises the steps: obtaining the analysis signal vertical guide number of a gravity and magnetic anomalous body; a tilt angle technology and a Laplacian equation are used for analyzing a vertical guide number of the analytic signal, and a boundary position is determined by calculating a difference perpendicular to a signal gradient direction; identifying the position and shape features of the gravity and magnetic anomalous body boundary to obtain fracture features; calculating analytic signals and curvatures of a gravity and magnetic anomaly field and an upward extension field of the gravity and magnetic anomaly body, and quantitatively extracting the top surface depth and the structure index of the boundary of the gravity and magnetic anomaly body to obtain the property of the fracture feature; according to the method, the Laplacian equation is introduced to deeply analyze the vertical guide number of the analysis signal, and only the first-order vertical guide number of the potential field needs to be calculated, so that the influence of high-frequency noise is reduced to a certain extent, and a basis is provided for subsequently determining the boundary position of the gravity and magnetic anomalous body.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of geophysical exploration, and particularly relates to a method, device, equipment and medium for boundary identification and determination of fracture characteristics. BACKGROUND

[0002] In the field of geophysical exploration, the analysis of gravity and magnetic anomalies is a key tool for identifying fractures and igneous rocks. They not only help us to delineate the subsurface structure, but also are essential for inferring the key characteristics of these structures. However, since gravity and magnetic prospecting is essentially a volumetric prospecting method, the data obtained is often a superposition of anomalies from different depths. This means that not all fractures and igneous rocks can be clearly visible in gravity and magnetic anomaly data, especially those with small size and small density or magnetic difference.

[0003] In order to improve the interpretation ability of gravity and magnetic anomalies, various information enhancement techniques have been developed, such as step-by-step stripping method, function approximation method, wavelet transform method, etc. The development of these techniques has significantly improved the accuracy of interpreting gravity and magnetic field information, but they are still insufficient in dealing with some complex superimposed or buried structures. The current mainstream methods, such as the source edge detection method (SED), the source parameter imaging method (SPI), the Euler deconvolution method (EULER) and the feature vector method (LFA), are mainly based on the derivatives and transformations of gridded potential field data. Although these methods are effective in some cases, their identification ability and depth extraction accuracy are still limited when dealing with structures with weak density and magnetic characteristics or similar characteristics. SUMMARY

[0004] In view of the problems in the background art, the present application provides a method, device, equipment and medium for boundary identification and determination of fracture characteristics.

[0005] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for boundary identification and determination of fracture characteristics, comprising:

[0007] obtaining the vertical derivative of the analytical signal of the gravity and magnetic anomaly body;

[0008] analyzing the vertical derivative of the analytical signal using the tilt angle technique and the Laplace equation, and determining the boundary position by calculating the difference perpendicular to the signal gradient direction;

[0009] identifying the position and shape characteristics of the boundary of the gravity and magnetic anomaly body to obtain the fracture characteristics;

[0010] calculating the analytical signal and curvature of the gravity and magnetic anomaly field and its upward continuation field of the gravity and magnetic anomaly body, and quantitatively extracting the top depth and structural index of the boundary of the gravity and magnetic anomaly body to obtain the properties of the fracture characteristics.

[0011] Furthermore, determining the boundary location includes:

[0012] Calculate the horizontal derivative of the gravity and magnetic anomaly field to determine the horizontal location of the boundary.

[0013] The first-order vertical derivative of the horizontal derivative is calculated using the Laplace equation to determine the boundary vertical information.

[0014] Calculate the tilt gradient of the first-order vertical derivative of the horizontal derivative to identify weak boundary anomalies.

[0015] Furthermore, the identification of the boundary information of the gravity and magnetic anomaly includes:

[0016] The gradient band of the gravity and magnetic anomaly is used as the extreme value band of the horizontal derivative, and the boundary position is delineated using the eigenvector method.

[0017] Furthermore, the sliding window of the eigenvector method is 3×3.

[0018] Furthermore, the boundary location is determined using the eigenvector method, including:

[0019] S31. Calculate the binomial coefficients based on the preset sliding window size;

[0020] S32. Calculate the most negative curvature of each window and determine whether the most negative curvature is less than zero. If yes, proceed to step S33; otherwise, proceed to step S35.

[0021] S33. Calculate the feature vector of each window, and calculate the center point based on the feature vector;

[0022] S34. Determine whether the distance from the center point to the center point of the window is less than a preset threshold. If yes, save the center point coordinates of the sliding window; otherwise, delete the center point coordinates of the sliding window.

[0023] S35. Move the sliding window according to the preset step size, and repeat step S31 until the entire image is traversed.

[0024] S36. Output the coordinates of the center point of all saved sliding windows.

[0025] Furthermore, the top surface depth and structural index of the gravity and magnetic anomaly boundary are quantitatively extracted, including:

[0026] Calculate the analytical signal and curvature of the gravity and magnetic anomaly field of the gravity and magnetic anomaly body;

[0027] The depth of the top surface is calculated based on the first and second derivatives of the analytical signal and the curvature.

[0028] The construction index is calculated based on the top surface depth.

[0029] Furthermore, the top surface depth is calculated based on the first and second derivatives of the analytical signal, the curvature, and the upward continuation technique.

[0030] Secondly, the present invention proposes an apparatus for identifying the boundary of a research area and determining fracture features, comprising:

[0031] The analytical signal vertical guide acquisition module is used to acquire the analytical signal vertical guide of the gravity and magnetic anomaly.

[0032] The analytical signal vertical derivative analysis module is used to analyze the vertical derivative of analytical signals using tilt angle technology and the Laplace equation, and to determine the boundary position by calculating the difference perpendicular to the signal gradient direction.

[0033] The boundary recognition module is used to identify the location and shape characteristics of the boundary of the gravity and magnetic anomaly to obtain fracture characteristics;

[0034] The top surface depth and structural index calculation module is used to calculate the analytical signal and curvature of the gravity and magnetic anomaly field and its extended field of the gravity and magnetic anomaly, quantitatively extract the top surface depth and structural index of the boundary of the gravity and magnetic anomaly, and obtain the properties of the fracture characteristics.

[0035] Thirdly, the present invention proposes an apparatus including a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and the processor executes the above-described method for boundary identification and determination of fracture features when executing the computer instructions.

[0036] Fourthly, the present invention proposes a computer-readable storage medium storing computer instructions thereon, which, when executed, can realize the above-mentioned method for boundary identification and determination of fracture characteristics.

[0037] The beneficial effects of this invention are:

[0038] The method of this invention conducts in-depth analysis of the vertical derivative of the obtained analytical signal by introducing the Laplace equation. It only requires the calculation of the first-order vertical derivative of the potential field, which reduces the influence of high-frequency noise to a certain extent. This provides a basis for accurately determining the boundary position of the gravity and magnetic anomaly. Based on the analytical signal and curvature, and combined with upward continuation technology, the top surface depth and structural index of the gravity and magnetic anomaly boundary are quantitatively extracted. This can effectively determine the fracture characteristics in the inversion model and provide a more accurate measurement method for underground structural features, making it widely applicable in fields such as geological exploration and mineral resource assessment.

[0039] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart of a method for boundary identification and determination of fracture features according to the present invention;

[0042] Figure 2 This is a parameter table for a study area model according to the present invention;

[0043] Figure 3 This is a schematic diagram of gravity anomaly data according to the present invention;

[0044] Figure 4 This is a schematic diagram of an information enhancement result according to the present invention;

[0045] Figure 5 This is a parameter table for a study area model according to the present invention;

[0046] Figure 6 This is a schematic diagram of magnetic anomaly data according to the present invention;

[0047] Figure 7 This is a schematic diagram of an information enhancement result according to the present invention;

[0048] Figure 8 This is a parameter table for a complex model of a research area according to the present invention;

[0049] Figure 9 This is a schematic diagram of the positional relationship of a model according to the present invention;

[0050] Figure 10 This is a three-dimensional top view of different information enhancement methods according to the present invention;

[0051] Figure 11 These are cross-sectional results of different information enhancement methods according to the present invention;

[0052] Figure 12 This is a parameter table for a magnetic three-block model of a research area according to the present invention;

[0053] Figure 13 This is a schematic diagram of the boundary position of a magnetic anomaly according to a model of the present invention;

[0054] Figure 14 The tilt angle identification result of the vertical derivative of the analytical signal according to the model of the present invention;

[0055] Figure 15 The depth result is calculated by this method using the model according to the present invention.

[0056] Figure 16 The constructed index result is calculated by this method using the model according to the present invention;

[0057] Figure 17 This is a parameter table for a complex model of a research area according to the present invention;

[0058] Figure 18 This is a schematic diagram of a magnetic anomaly according to a model based on the present invention;

[0059] Figure 19 The depth result is obtained using the Euler deconvolution method according to a model based on the present invention.

[0060] Figure 20 The depth result is calculated by this method using the model according to the present invention;

[0061] Figure 21 The constructed index result is calculated by this method using the model according to the present invention;

[0062] Figure 22 This is a schematic diagram of the structure of a device for boundary identification and fracture feature determination according to the present invention;

[0063] Figure 23 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Refer to the instruction manual appendix Figure 1 As shown, this invention proposes a method for boundary identification and fracture feature determination, applicable to various geological exploration scenarios such as oil and gas exploration, mineral resource assessment, groundwater investigation, and geological disaster prevention, including the following steps:

[0066] S1. Obtain the vertical derivative of the analytical signal of the gravity and magnetic anomaly;

[0067] In this process, data on gravity and magnetic anomalies are collected using instruments such as gravimeters and magnetometers, and the collected data are processed to obtain the vertical derivative of the analytical signal.

[0068] S2. Analyze the vertical derivative of the analytical signal using the tlit angle technique and the Laplace equation, and determine the boundary position by calculating the difference perpendicular to the signal gradient direction;

[0069] Specifically, the vertical derivative of the analytical signal is analyzed using the tlit angle technique and the Laplace equation. The boundary position is determined by calculating the difference perpendicular to the signal gradient direction, including the following steps:

[0070] S21. Calculate the horizontal derivative of the gravity and magnetic anomaly field to determine the horizontal boundary position. The expression is:

[0071]

[0072] Where f represents gravity or magnetization polar anomaly;

[0073] In existing technology, the first-order vertical derivative for calculating the horizontal derivative is expressed as:

[0074]

[0075] The gradient of the first-order vertical derivative of the horizontal derivative is expressed as:

[0076]

[0077] Where x, y, and z are the coordinate values ​​in three directions of a three-dimensional rectangular coordinate system.

[0078] Specifically, in the prior art, refer to the appendix to the specification. Figure 8 To be continued Figure 11 As shown, based on the model parameters of the study area (such as...) Figure 8 The target area is 100km × 100km (100km horizontally and 100km vertically), with a grid size of 100 × 100 and a grid spacing of 1000m in both directions. This allows for the acquisition of magnetic anomaly data for the study area (e.g., ...). Figure 9 ), and based on this anomalous data, information enhancement (such as...) is performed on the study area. Figure 10 , 11 As shown). Figure 10As shown, the THDR method clearly identifies the boundary positions of shallower blocks B and C. However, because this method does not incorporate vertical derivatives, the boundary information of blocks D and E is obscured, and the boundary information of isolated block A, which produces small amplitudes, is also unclear. The THETA, TDR, and ILP methods, due to the incorporation of derivative transformations, can clearly identify the information of isolated block A, but their ability to identify the combination of stacked blocks C, D, and E is poor. While the TDHR method identifies more boundary information, it clearly generates many false boundary information, leading to incorrect judgments about the combined distribution of the model. The TAHG method performs better than the previous methods, identifying some boundary information of block E within the stacked blocks, but its performance is poor for block D.

[0079] like Figure 11 As shown, Figures a and b illustrate the distribution of these five anomalous blocks in sections AA1 and BB1, respectively. Figures c and d show the THETA (dashed line) and TDR (solid line) results for the corresponding sections AA1 and BB1, respectively; Figures e and f show the TDHR (dashed line) and ILP (solid line) results; and Figures g and h show the TAHG (dashed line) and THVH (solid line) results. In the THETA method, the minimum amplitude represents boundary information, and in the TDR method, the zero amplitude represents boundary information. The boundary position information identified by these methods overlaps. The boundary positions of blocks A and B have a certain extension compared to the theoretical model positions, but it is difficult to identify the boundary information of superimposed blocks. In the TDHR method, the minimum amplitude represents the boundary position, and in the ILP method, the maximum amplitude represents the boundary position. From the cross-section, the TDHR method clearly and accurately depicts the boundary position of the blocks, but identification results also appear in places where there are no blocks. The cross-section results of the ILP method are irregular, and the maximum values ​​are not obvious, so it is difficult to determine the boundary position. In the TAHG method and the tilt angle of the vertical derivative of the analytical signal, the maximum amplitude corresponds to the boundary position. Although the maximum value of the TAHG method is larger, the amplitude change of the tilt angle of the vertical derivative of the analytical signal is more obvious. The TAHG method has difficulty identifying the boundary position of block D, while the tilt angle of the vertical derivative of the analytical signal can identify it.

[0080] As can be seen from the gradient formula above, during the processing, it is necessary to calculate the first and second vertical derivatives of the potential field in the frequency domain, which is greatly affected by high-frequency noise.

[0081] Therefore, this invention introduces the Laplace equation, so that the method only needs to calculate the first derivative:

[0082] The Laplace equation is written in detail as follows:

[0083]

[0084] The first derivative of the potential field also satisfies the Laplace equation:

[0085]

[0086] but:

[0087]

[0088] Similarly:

[0089]

[0090] set up but:

[0091]

[0092] in but:

[0093]

[0094] S22. Calculate the first-order vertical derivative of the horizontal derivative using the Laplace equation to determine the boundary vertical information;

[0095] The formula for the first-order vertical derivative of the horizontal derivative can be rewritten as:

[0096]

[0097] S23. Calculate the tilt gradient of the first-order vertical derivative of the horizontal derivative to identify weak boundary anomalies. The expression is:

[0098]

[0099] Where x, y, and z are the coordinate values ​​in three directions of a three-dimensional rectangular coordinate system.

[0100] By introducing the Laplace equation, only the first-order vertical derivative of the potential field needs to be calculated, which reduces the impact of high-frequency noise to some extent.

[0101] Calculating the horizontal derivative of the gravity and magnetic anomaly field ensures the accuracy of the horizontal position of the boundary; calculating the first vertical derivative of the horizontal derivative enhances the ability to identify vertical information; and calculating the tilt gradient highlights the ability to represent weak information.

[0102] For example, refer to the appendix to the instruction manual. Figure 2 To be continued Figure 4 As shown, the model parameters of the study area (such as...) Figure 2The target area is 100km × 60km (100km horizontally and 60km vertically), with a grid size of 100 × 60 and a grid spacing of 1000m in both directions. This allows for the acquisition of gravity anomaly data for the study area (e.g., Figure 3 ), and based on this anomalous data, information enhancement (such as...) is performed on the study area. Figure 4 (As shown).

[0103] Refer to the instruction manual appendix Figure 5 To be continued Figure 7 As shown, the model parameters of the study area (such as...) Figure 5 The target area is 100km × 60km (100km horizontally and 60km vertically), with a grid size of 100 × 60, and the horizontal and vertical grid spacing is the same at 1000m. This allows for the acquisition of magnetic anomaly data for the study area (e.g., Figure 6 ), and based on this anomalous data, information enhancement (such as...) is performed on the study area. Figure 7 ).

[0104] S3. Identify the location and shape characteristics of the boundary of the gravity and magnetic anomaly to obtain fracture characteristics;

[0105] In step S3, the location and shape characteristics of the boundary are determined, and then the fracture characteristics can be obtained, because the main characteristics of the fracture are its location and shape.

[0106] Specifically, the gradient band of the gravity and magnetic anomaly is used as the extreme value band of the horizontal derivative, and the boundary position is delineated using the eigenvector method.

[0107] The eigenvector method uses a 3×3 sliding window to identify boundaries, and specifically includes the following steps:

[0108] S31. Calculate the binomial coefficients based on the preset sliding window size;

[0109] S32. Calculate the most negative curvature of each sliding window and determine whether the most negative curvature is less than zero. If yes, proceed to step S33; otherwise, proceed to step S35.

[0110] S33. Calculate the feature vector of each sliding window, and calculate the center point based on the feature vector;

[0111] S34. Determine whether the distance from the center point to the center point of the sliding window is less than a preset threshold. If yes, save the coordinates of the center point of the sliding window; otherwise, delete the coordinates of the center point of the sliding window.

[0112] S35. Move the sliding window according to the preset step size, return to step S31, and repeat until the entire image is traversed.

[0113] S36. Output the coordinates of the center point of all saved sliding windows.

[0114] For example, using a 3×3 sliding window to identify boundaries includes the following steps:

[0115] Fit a quadratic polynomial of a parabola using the values ​​of the nine nodes on the window, as shown in the following expression:

[0116]

[0117] The expressions for each coefficient are as follows:

[0118]

[0119] Where Δx and Δy represent the mesh spacing in the x and y directions, and g represents the value at each mesh node. The curvature matrix of the parabola is a binomial Hessian matrix, i.e.:

[0120]

[0121] The eigenvalues ​​of the matrix are:

[0122]

[0123] Where, λ + For the most positive curvature, λ - The most negative curvature is λ. - These are important parameters for calculating the boundary and depth. Simultaneously, the eigenvectors satisfy:

[0124]

[0125] Solving for:

[0126]

[0127] Let x = e x t,y=e y t, and substitute it into the quadratic polynomial to obtain the center point (x0, y0):

[0128]

[0129] S4. Calculate the analytical signal and curvature of the gravity and magnetic anomaly field and its extended field of the gravity and magnetic anomaly body, quantitatively extract the top surface depth and structural index of the boundary of the gravity and magnetic anomaly body, and obtain the properties of the fracture characteristics.

[0130] Top surface depth and structural index are properties of the identified boundary, and the properties of the identified boundary reflect, to some extent, the properties of the fracture characteristics in reality.

[0131] Refer to the instruction manual appendix Figure 12 To be continuedFigure 21 As shown, the model parameters of the study area (such as...) Figure 12 The target area is 600km × 300km (600km horizontally and 300km vertically), with a grid size of 300 × 150, and the same grid spacing of 2000m in both directions. This allows us to obtain the depth and structural indices (such as...) of the study area. Figure 15 , Figure 16 ).

[0132] like Figure 14 As shown, the tilt angle of the vertical derivative of the analytical signal accurately extracted the boundary positions of the three magnetic anomalies. Figure 15 , 16 As shown, anomaly A is a horizontal thin plate with a construction index of 1, and anomaly C is a contact zone with a construction index of 0. This method allows for the extraction of depth without specifying a construction index initially, resulting in a smaller error between the extracted depth and the actual depth. The construction indices of anomalies B and C extracted by this method range from 0 to 0.3, which is consistent with the construction index of the contact zone. The construction index of anomaly A ranges from 0.6 to 1.3, matching the structural characteristics of a horizontal thin plate.

[0133] Based on the model parameters of the study area (such as...) Figure 18 The target area is 161km × 101km (161km horizontally and 101km vertically), with a grid size of 161 × 101 and a grid spacing of 1000m in both directions. This allows for the acquisition of the depth and structural indices (e.g., [missing information]) of the study area. Figure 20 , Figure 21 ).

[0134] Depend on Figure 19 As shown, due to the influence of adjacent anomalies, the calculation results of the Euler deconvolution method do not match the model well. Figure 20 The boundary depth calculated by this method can match the actual depth well, with an error within 10%. Figure 21 The structural indices calculated by this method are as follows: the structural indices of anomaly A are between 0.5 and 0.8, which are consistent with the structural characteristics of a horizontal thin plate; the structural indices of anomalies B and C are between 0 and 0.3, which are consistent with the structural indices of the contact zone.

[0135] Specifically, the quantitative extraction of the top surface depth and structural index of the boundary of a gravity and magnetic anomaly includes the following steps:

[0136] S41. Calculate the analytical signal and curvature of the gravity and magnetic anomaly field of the gravity and magnetic anomaly body;

[0137] The analytic signal expression is:

[0138]

[0139] For the anomaly generated at (h,z) by a gravity and magnetic anomaly located at (h0,z0), H = (h – h0), Z = (z – z0), and a is a constant; for magnetic bodies, the structural index N is equal to 0, 1, 2, 3, representing contact zone, vertical dike, horizontal or vertical cylinder, and sphere, respectively; the structural index of gravity anomalies is the corresponding magnetic anomaly minus 1.

[0140] S42. Calculate the top surface depth based on the first and second derivatives of the analytic signal and the curvature;

[0141] S421. Calculate the first and second derivatives based on the analytical signal expression in step S41:

[0142] First derivative:

[0143] Second derivative:

[0144] Let h = h0, z = 0, then:

[0145] Equation (1) can be rewritten as:

[0146] Equation (2) can be rewritten as:

[0147] According to the curvature formula:

[0148]

[0149] S422, Calculate the depth of the top surface;

[0150] Combining equations (3), (4), and (5) above, we get:

[0151]

[0152] As can be seen from the above expression (6), the above steps for calculating the depth of the top surface require a construction index to be given manually in order to calculate the depth of the boundary point. However, the selection of the construction index directly affects the accuracy of the depth. Therefore, in order to eliminate the artificiality, an upward extension field can be introduced by the upward extension technique.

[0153] Specifically, if we extend upwards by Δz, then expression (6) can be rewritten as:

[0154]

[0155] Combining equations (6) and (7) above, we get:

[0156]

[0157] S43. Calculate the construction index based on the top surface depth;

[0158] Substituting the above expression (8) back into equation (6), we can construct the exponential expression as follows:

[0159]

[0160] or

[0161]

[0162] This invention introduces the Laplace equation to conduct in-depth analysis of the vertical derivative of the obtained analytical signal. Only the first-order vertical derivative of the potential field needs to be calculated, which reduces the influence of high-frequency noise to a certain extent. This provides a foundation for accurately determining the boundary location of gravity and magnetic anomalies. Based on the analytical signal and curvature, and combined with upward continuation technology, the top surface depth and structural index of the gravity and magnetic anomaly boundary are quantitatively extracted. This can effectively determine the fracture characteristics in the inversion model and provide a more accurate measurement method for underground structural features, making it widely applicable in fields such as geological exploration and mineral resource assessment.

[0163] Based on the same inventive concept, refer to the appendix to the specification. Figure 22 As shown, the present invention also proposes a device for boundary identification and determination of fracture features, comprising:

[0164] The analytical signal vertical guide acquisition module 110 is used to acquire the analytical signal vertical guide of the gravity and magnetic anomaly.

[0165] The analytical signal vertical derivative analysis module 120 is used to analyze the analytical signal vertical derivative using tilt angle technology and Laplace equation, and to determine the boundary position by calculating the difference perpendicular to the signal gradient direction.

[0166] Boundary recognition module 130 is used to identify the position and shape characteristics of the boundary of the gravity and magnetic anomaly to obtain fracture characteristics;

[0167] The top surface depth and structural index calculation module 140 is used to calculate the analytical signal and curvature of the gravity and magnetic anomaly field and its extended field of the gravity and magnetic anomaly body, quantitatively extract the top surface depth and structural index of the boundary of the gravity and magnetic anomaly body, and obtain the properties of the fracture characteristics.

[0168] Based on the same inventive concept, this invention also proposes a computer-readable storage medium storing computer instructions, which, when executed, can realize the aforementioned method for boundary identification and determination of fracture characteristics.

[0169] Based on the same inventive concept, refer to the appendix to the specification. Figure 23As shown, the present invention also proposes a device including a memory and a processor, wherein the memory stores computer instructions that can be executed on the processor, and the processor executes the above-described method for boundary identification and determination of fracture features when executing the computer instructions.

[0170] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0171] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for boundary identification and determination of fracture features, characterized in that, include: Obtain the vertical derivative of the analytical signal of a gravity / magnetic anomaly; The vertical derivative of the analytical signal is analyzed using the tilt angle technique and the Laplace equation, and the boundary position is determined by calculating the difference perpendicular to the signal gradient direction. Identify the location and shape characteristics of the boundary of the gravity and magnetic anomaly to obtain fracture characteristics; The analytical signals and curvature of the gravity and magnetic anomaly field and its extended field of the gravity and magnetic anomaly are calculated. The top surface depth and structural index of the boundary of the gravity and magnetic anomaly are quantitatively extracted to obtain the properties of the fracture characteristics.

2. The method for boundary identification and determination of fracture features according to claim 1, characterized in that, Determining the boundary position includes: Calculate the horizontal derivative of the gravity and magnetic anomaly field to determine the horizontal location of the boundary. The first-order vertical derivative of the horizontal derivative is calculated using the Laplace equation to determine the vertical information of the boundary. Calculate the tilt gradient of the first-order vertical derivative of the horizontal derivative to identify weak boundary anomalies.

3. The method for boundary identification and determination of fracture features according to claim 1, characterized in that, The identification of the boundary information of the gravity and magnetic anomaly includes: The gradient band of the gravity and magnetic anomaly is used as the extreme value band of the horizontal derivative, and the boundary position is delineated using the eigenvector method.

4. The method for boundary identification and determination of fracture features according to claim 3, characterized in that, The boundary location is determined using the eigenvector method, including: S31. Calculate the binomial coefficients based on the preset sliding window size; S32. Calculate the most negative curvature of each sliding window and determine whether the most negative curvature is less than zero. If yes, proceed to step S33; otherwise, proceed to step S35. S33. Calculate the feature vector of each sliding window, and calculate the center point based on the feature vector; S34. Determine whether the distance from the center point to the center point of the sliding window is less than a preset threshold. If yes, save the coordinates of the center point of the sliding window; otherwise, delete the coordinates of the center point of the sliding window. S35. Move the sliding window according to the preset step size, return to step S31, and repeat until the entire image is traversed. S36. Output the coordinates of the center point of all saved sliding windows.

5. The method for boundary identification and determination of fracture features according to claim 4, characterized in that, The sliding window of the eigenvector method is 3×3.

6. The method for boundary identification and determination of fracture features according to claim 1, characterized in that, Quantitative extraction of the top surface depth and structural index of the boundary of a gravity and magnetic anomaly, including: Calculate the analytical signal and curvature of the gravity and magnetic anomaly field of the gravity and magnetic anomaly body; The depth of the top surface is calculated based on the first and second derivatives of the analytical signal and the curvature. The construction index is calculated based on the top surface depth.

7. The method for boundary identification and determination of fracture features according to claim 6, characterized in that, The top surface depth is calculated based on the first and second derivatives of the analytical signal, the curvature, and the upward continuation technique.

8. A device for boundary identification and determining fracture characteristics, characterized in that, include: The analytical signal vertical guide acquisition module is used to acquire the analytical signal vertical guide of the gravity and magnetic anomaly. The analytical signal vertical derivative analysis module is used to analyze the vertical derivative of analytical signals using tilt angle technology and the Laplace equation, and to determine the boundary position by calculating the difference perpendicular to the signal gradient direction. The boundary recognition module is used to identify the location and shape characteristics of the boundary of the gravity and magnetic anomaly to obtain fracture characteristics; The top surface depth and structural index calculation module is used to calculate the analytical signal and curvature of the gravity and magnetic anomaly field and its extended field of the gravity and magnetic anomaly, quantitatively extract the top surface depth and structural index of the boundary of the gravity and magnetic anomaly, and obtain the properties of the fracture characteristics.

9. A device comprising a memory and a processor, wherein the memory stores computer instructions executable on the processor, characterized in that, When the processor executes the computer instructions, it performs a method for boundary identification and determination of fracture features as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer instructions thereon, characterized in that, When computer instructions are executed, a method for boundary identification and determination of fracture characteristics as described in any one of claims 1 to 7 can be implemented.

Images